In a conventional retail, catalogue, or library environment, customers are able to browse quickly and conveniently through large physical displays of products, while they inspect images, read words, listen to music, and/or engage in other reviewing activities, until they find the specific product most suitable for their purposes, needs, interests, or tastes. Typical examples of such environments include greeting card shops and video rental stores. Under these conventional circumstances, customers can and do exercise their discriminating judgments and mental processes to make selections following direct physical surveillance of the products.
Recently, machines and systems have been introduced that replace these large physical product displays by storing data relating to the products in magnetic or optical storage devices. An example of such machines are the social expression product machines which have become popular in recent years because they eliminate many of the problems associated with displaying numerous categories and sub-categories of social expression products. Some of these problems include the space required for displaying such a variety of social expression products, the resulting inventory requirements, and potential customer confusion resulting from the wide variety of social expression products from which to choose. Similarly, large physical displays of products may be replaced by a single central library of products or data relating to the products that can be selected electronically by a remote customer employing interactive means and then transmitted for display. The problem in both such instances is to allow the customer to enter data that enables the system to retrieve products or data relating to the products from a non-visible library which are likely to suit the customer's purposes, needs, interests, or tastes.
Social expression product machines typically comprise a computer operated vending machine, a display screen, and a keyboard input terminal. A variety of available social expression product designs are stored in the computer. By means of the display screen, the computer prompts a customer to provide design criteria, or to select from a menu of computer-provided design criteria, indicative of appropriate social expression product designs for that customer. The keyboard input terminal is used to select or present the design criteria.
The computer uses the provided or selected design criteria to identify appropriate social expression product designs from the variety of available social expression product designs stored therein, generally by techniques which search for and identify those designs whose specified properties are exactly matched to the customer input design criteria. From these identified designs, the customer is directed to select one design, which the computer-driven vending machine prints on blank card stock and dispenses to the customer. In this manner, the customer can retrieve and review portions of the data on a video screen and audio system, by giving instructions on a keyboard or touchscreen that is connected by a programmed computer to the storage devices holding the data.
In simple situations involving such machines, the retrieval of the data is easily managed by conventional methods. For example, in the case of inputting or selecting a title, an object image or a few descriptive words can communicate to a machine all of the information required to specify the data file or files containing information that a customer wants to retrieve and display. Product characteristics are identified by allowable combinations of customer entered data. The computer can be programmed to retrieve the file or files that the user specifies, either by accessing known locations in a data storage device or by searching a database to find the files whose identities match the descriptive words input by the customer. An example of a machine and method that accesses data from known storage locations is shown in U.S. Pat. No. 3,757,037 to Norman Bialek. An example of a machine and method that searches a database to find files whose identities match descriptive words is shown in U.S. Pat. No. 5,056,029 to Thomas G. Cannon.
The Cannon patent discloses a method wherein a customer is queried to elicit responses, in the form of occasion parameters, each of which relates to the customer's intended communication purpose. Social expression cards which may be selected for manufacture are stored, not physically, but in the form of design data held in high density magnetic or optical storage. The design data is identifiable by some unique combination of occasion parameters. Following the entry of customer responses, the computer retrieves and displays a set of card files which includes all of the stored card designs having occasion parameters which identically match those entered by the customer. While the card vending machine shown in the Cannon patent provides an efficient means for storing many different types of social expression cards and for retrieving and displaying those card designs which match a customer's criteria, that machine, as well as other known machines, suffers from several drawbacks.
One drawback is that the present machines can retrieve and display only those card designs that are identified by labels or descriptors that match exactly the criteria specified by the customer. However, some card designs can convey messages so broad in scope that they cannot be defined exclusively with selected descriptors. These designs may be applicable to many kinds of sending situations, especially when they are capable of being modified by the customer. At the same time, other card designs may have descriptors that only correspond partially to a given set of customer criteria but may still be eminently suitable. Because the present card vending machines are limited in that they require an exact match between customer criteria and card descriptors, they cannot use a large database of card designs to its fullest potential in meeting customer needs.
Indeed, the number of card designs that must be stored in the database of one of the presently available machines is extremely large in relation to the number of different combinations of customer needs that it can meet. Because of the exact correspondence that is required between the card descriptors and the customer criteria, the number of stored card designs must be equal to the number of possible combinations of the various criteria that a customer can specify, multiplied by the average number of card designs that a vendor would want to display in response to a particular criteria combination. For instance, if the customer were given five possible criteria options to choose from within each of four card descriptors, 625 (=5.sup.4) combinations of customer-selected criteria would be possible. If an average of ten card designs were made available for each combination, then a total of 6,250 card designs would be required in the database.
Another drawback is that such machines restrict the identities of product data files to fixed combinations of customer entry data. Many buyers of products and users of information cannot easily provide the exact word or words necessary for retrieving data either from known storage locations or by database searching. The suitability of products, especially those that have rich aesthetic, intellectual, or entertainment values, often cannot be described by single combinations of descriptive words. Thus, it may be necessary to provide the capability for several different forms or contents of customer entry data to access and retrieve a given product data file. For example, a customer may be able to specify only a few criteria for products that he wants to view, while those products are identified by many descriptive words. In such a case, a customer's specific criteria may be considered as suggestive only and a wide range of product files may be shown to him, some of which have very few, if any, of the exact criteria specified by the customer. As a result, some data files may apply to and ought to be retrievable in response to many different sets of customer purposes, needs, interests, or tastes.
More importantly, on many occasions, a given product design may possess a very high degree of applicability with respect to one selection criterion input by a customer, but lower or very low degrees of applicability with respect to other criteria. On other occasions, a given product design may be highly applicable with respect to selection criteria that really matter to the customer but non-applicable with respect to other criteria that matter little. On still other occasions, the customer may specify a limited set of selection criteria that cannot be matched to any stored product designs because the designs are characterized by a much larger set of descriptors. In the general case where customer inputs comprise multiple selection criteria, the set of criteria will possess varying degrees of correspondence and closeness to the set of descriptors used to describe the properties of the stored product designs. The problem to be solved is to identify for retrieval some subset of designs whose overall suitability is judged to be the best.
In one solution, the product designs may be designated as having varying degrees of applicability or suitability for a particular set of customer criteria, rather than being designated as either suitable or not suitable. In that case, customers may prefer to see product designs of such varying suitability in the order of their anticipated suitabilities, from the highest to the lowest. Conversely, different customers may prefer to see different numbers of product designs having a range of suitabilities. All of the aforementioned circumstances and needs can best be served by a system which, rather than seeking to identify products whose characteristics exactly match customer specifications, embodies one or more kinds of suitability data for the purpose of selectively retrieving some subset of best fitting or most appropriate products or product data files in response to customer data entry.